Open Journal of Applied Sciences

Volume 5, Issue 6 (June 2015)

ISSN Print: 2165-3917   ISSN Online: 2165-3925

Google-based Impact Factor: 0.92  Citations  h5-index & Ranking

Improved Quantum-Behaved Particle Swarm Optimization

HTML  XML Download Download as PDF (Size: 305KB)  PP. 240-250  
DOI: 10.4236/ojapps.2015.56025    3,674 Downloads   5,223 Views  Citations
Author(s)

ABSTRACT

To enhance the performance of quantum-behaved PSO, some improvements are proposed. First, an encoding method based on the Bloch sphere is presented. In this method, each particle carries three groups of Bloch coordinates of qubits, and these coordinates are actually the approximate solutions. The particles are updated by rotating qubits about an axis on the Bloch sphere, which can simultaneously adjust two parameters of qubits, and can automatically achieve the best matching of two adjustments. The optimization process is employed in the n-dimensional space [-1, 1]n, so this approach fits to many optimization problems. The experimental results show that this algorithm is superior to the original quantum-behaved PSO.

Share and Cite:

Li, J. (2015) Improved Quantum-Behaved Particle Swarm Optimization. Open Journal of Applied Sciences, 5, 240-250. doi: 10.4236/ojapps.2015.56025.

Cited by

[1] Tracking controller based on model prediction control for remotely operated vehicle for thruster fault
Journal of Marine Science and Technology, 2022
[2] Effect of potential well model for quantum heuristic algorithm: a comparative study and application
International Journal of Bio-Inspired …, 2022
[3] VR Panorama Mosaic Algorithm Based on Particle Swarm Optimization and Mutual Information
2020
[4] An improved quantum particle swarm photovoltaic multi‐peak mPPT method combined with Lévy flight
2020
[5] QPSO-model predictive control-based approach to dynamic trajectory tracking control for unmanned underwater vehicles
Ocean Engineering, 2018
[6] Production scheduling optimization method based on hybrid particle swarm optimization algorithm
Journal of Intelligent & Fuzzy Systems, 2018
[7] The Tracking Control of Unmanned Underwater Vehicles Based on QPSO-Model Predictive Control
Intelligent Robotics and Applications, 2017
[8] 基于改进粒子群算法的无人机三维航迹规划
西北工业大学学报, 2017
[9] Optimasi Penempatan Menara BTS Menggunakan Quantum-Behaved Particle Swarm Optimization
2016
[10] The improvement of particle swarm optimization
2016

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.